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Constraints to Increasing Agricultural Productivity in Nigeria: A Review

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There is a grow<strong>in</strong>g demand <strong>to</strong> weigh labor <strong>in</strong>puts for age and gender groups <strong>in</strong> Africa s<strong>in</strong>ce the<br />

roles of women <strong>in</strong> agriculture differ between places on the cont<strong>in</strong>ent. In some areas <strong>in</strong> <strong>Nigeria</strong>,<br />

on-farm activities are left <strong>to</strong> women. In other places, women engage ma<strong>in</strong>ly <strong>in</strong> cook<strong>in</strong>g and<br />

car<strong>in</strong>g for children. To better appreciate women’s roles and <strong>to</strong> estimate their farm labor<br />

productivity, diverse roles must be accounted for. Differentiation between women who are<br />

primarily housewives and women who are primarily farmers will ultimately affect estimation of<br />

labor productivity. Failure <strong>to</strong> account for differ<strong>in</strong>g roles may underestimate agricultural labor<br />

productivity.<br />

Table 7. Percentage of women perform<strong>in</strong>g specific farm activities, Kats<strong>in</strong>a and Kaduna states<br />

Farm<strong>in</strong>g activity<br />

Of related importance <strong>to</strong> gender issues <strong>in</strong> agricultural productivity is level of education. High<br />

illiteracy rates among women will limit adoption of improved farm technologies, while high<br />

literacy rates for both gender groups is expected <strong>to</strong> improve farmers’ ability <strong>to</strong> use <strong>in</strong>formation<br />

from extension services. This would enhance farm recordkeep<strong>in</strong>g for improved cost-and-returns<br />

evaluation and better track<strong>in</strong>g of market opportunities. Thus, education is expected <strong>to</strong> affect<br />

agricultural productivity. However, it is conceivable that with better education, farmers may seek<br />

better-pay<strong>in</strong>g nonfarm jobs for which they become suited.<br />

Low Access <strong>to</strong> <strong>Agricultural</strong> Credit<br />

Funtua<br />

(Kats<strong>in</strong>a state)<br />

Land preparation 17 80<br />

Ridg<strong>in</strong>g 0 30<br />

Plant<strong>in</strong>g 17 100<br />

Weed<strong>in</strong>g 0 80<br />

Fertilizer application 33 90<br />

Harvest<strong>in</strong>g 0 100<br />

Transport<strong>in</strong>g 33 100<br />

Zonkwa<br />

(Kaduna<br />

state)<br />

Source: NARP 1994.<br />

Note: Funtua is a Muslim community <strong>in</strong>habited largely by the<br />

Hausa/Fulani while Zonkwa is a Christian community,<br />

dom<strong>in</strong>ated by Jarma people.<br />

Access <strong>to</strong> agricultural credit has been positively l<strong>in</strong>ked <strong>to</strong> agricultural productivity <strong>in</strong> several<br />

studies. Yet this vital <strong>in</strong>put has eluded smallholder farmers <strong>in</strong> <strong>Nigeria</strong>. As shown <strong>in</strong> Table 8,<br />

cooperatives, friends, and family members dom<strong>in</strong>ate the sources of farm credit among the rural<br />

farmers surveyed <strong>in</strong> southwest <strong>Nigeria</strong>. However, the <strong>to</strong>tal amount of farm credit available from<br />

these sources is very limited <strong>in</strong> relation <strong>to</strong> the amounts that formal sources like banks would<br />

have offered. These results are re<strong>in</strong>forced by the studies shown <strong>in</strong> Tables 10 and 11.<br />

Table 8. Available sources of farm credit <strong>to</strong> sample of farmers, Oyo and Ogun states, southwest <strong>Nigeria</strong><br />

Source % respond<strong>in</strong>g *<br />

Cooperatives<br />

Informal (friends/family)<br />

Banks<br />

75<br />

75<br />

0<br />

Source: Phillip and Adetimir<strong>in</strong> 2001; * Multiple responses allowed.<br />

26

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